Literature Index

Use of the internet to support instruction in general and the use of statistical software in particular provides instructors and students with an opportunity to improve learning while maintaining effective use of limited classroom time. We have developed a Web site (http://power.education.uconn.edu/) that encompasses instruction in power analysis issues and teaches students and others how to use the nQuery Advisor© software to establish sample size for research designs ranging from the simple to the complex. The evaluation results of our Power Project Web site and materials are promising, and the purpose of this paper is to share our approach and materials with other instructors of statistics and research design.

The purpose of the project that formed the basis of the work reported herein was to provide students a series of web-based statistical readings designed to illustrate common statistical concepts via "real-life" educational research situations.

The most prominent characteristic of people's dealings with variability (that we are aware of to date) is their tendency to eliminate, or underestimate the dispersion of the data (e.g., Kareev, Arnon &amp; Horowitz-Zeliger, 2002), that is, the differences among individual observations and among means of samples from a population (Tversky &amp; Kahneman, 1971). One typically focuses on the average, and forgets about the individual differences in the material.<br><br>Shaughnessy and Pfannkuch (2002) report that when asked to analyze a set of data, many students just calculated a mean or a median. They claim that past teaching and textbooks concentrated heavily on such measures and neglected variation. Shaughnessy and Pfannkuch maintain, however, that variability is important. It exists in all processes. Understanding of variation is the central element of any definition of statistical thinking. They quote David Moore's slogan "variation matters" (p. 255).<br><br>In the history of statistics, the tendency to eliminate human variability was represented (in the first half of the 19th century) by Quetelet, who focused on regularities. According to Gigerenzer, et al. (1989), Quetelet understood variation within species as something akin to measurement- or replication-error: The average expressed the "essence" of humankind. "Variations from the average man were accidental - matters of chance - in the same sense that measurement errors were" (p. 142). Quetelet's conception of variation was diametrically different from Darwin's, who focused on variability itself and regarded variations from the mean as the crucial materials of evolution by natural selection.<br><br>One example of the tendency to ignore variability is obtained when assignment of probabilities (or weights) to a set of possible outcomes is called for. People often tend to distribute these probabilities equally over the available options (Falk, 1992; Lann &amp; Falk, 2002; Pollatsek, Lima &amp; Well, 1981; Zabell, 1988), employing what we call the uniformity heuristic. Equi-probability, or zero variability among the probabilities, is the simplest and easiest choice to fall back on.

Investigates students' understanding of the idea of average. Relationship between data and the average of the data; Confusion of the term with mode and median.